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Using rich and detailed data, this groundbreaking book explains why homelessness has become a crisis in America and reveals the structural conditions that underlie it. In Homelessness Is a Housing Problem, Gregg Colburn and Clayton Page Aldern seek to explain the substantial regional variation in rates of homelessness in cities across the United States. In a departure from many analytical approaches, Colburn and Aldern shift their focus from the individual experiencing homelessness to the metropolitan area. Using accessible statistical analysis, they test a range of conventional beliefs about what drives the prevalence of homelessness in a given city—including mental illness, drug use, poverty, weather, generosity of public assistance, and low-income mobility—and find that none explain the regional variation observed across the country. Instead, housing market conditions, such as the cost and availability of rental housing, offer a far more convincing account. With rigor and clarity, Homelessness Is a Housing Problem explores U.S. cities' diverse experiences with housing precarity and offers policy solutions for unique regional contexts.
United States. Federal Housing Administration. Division of Research and Statistics. Survey and Analysis Section
Author : United States. Federal Housing Administration. Division of Research and Statistics. Survey and Analysis Section Publisher : Page : 68 pages File Size : 39,20 MB Release : 1948 Category : ISBN :
Author : Katharine G. Abraham Publisher : University of Chicago Press Page : 502 pages File Size : 36,44 MB Release : 2022-03-11 Category : Business & Economics ISBN : 022680125X
Introduction.Big data for twenty-first-century economic statistics: the future is now /Katharine G. Abraham, Ron S. Jarmin, Brian C. Moyer, and Matthew D. Shapiro --Toward comprehensive use of big data in economic statistics.Reengineering key national economic indicators /Gabriel Ehrlich, John Haltiwanger, Ron S. Jarmin, David Johnson, and Matthew D. Shapiro ;Big data in the US consumer price index: experiences and plans /Crystal G. Konny, Brendan K. Williams, and David M. Friedman ;Improving retail trade data products using alternative data sources /Rebecca J. Hutchinson ;From transaction data to economic statistics: constructing real-time, high-frequency, geographic measures of consumer spending /Aditya Aladangady, Shifrah Aron-Dine, Wendy Dunn, Laura Feiveson, Paul Lengermann, and Claudia Sahm ;Improving the accuracy of economic measurement with multiple data sources: the case of payroll employment data /Tomaz Cajner, Leland D. Crane, Ryan A. Decker, Adrian Hamins-Puertolas, and Christopher Kurz --Uses of big data for classification.Transforming naturally occurring text data into economic statistics: the case of online job vacancy postings /Arthur Turrell, Bradley Speigner, Jyldyz Djumalieva, David Copple, and James Thurgood ;Automating response evaluation for franchising questions on the 2017 economic census /Joseph Staudt, Yifang Wei, Lisa Singh, Shawn Klimek, J. Bradford Jensen, and Andrew Baer ;Using public data to generate industrial classification codes /John Cuffe, Sudip Bhattacharjee, Ugochukwu Etudo, Justin C. Smith, Nevada Basdeo, Nathaniel Burbank, and Shawn R. Roberts --Uses of big data for sectoral measurement.Nowcasting the local economy: using Yelp data to measure economic activity /Edward L. Glaeser, Hyunjin Kim, and Michael Luca ;Unit values for import and export price indexes: a proof of concept /Don A. Fast and Susan E. Fleck ;Quantifying productivity growth in the delivery of important episodes of care within the Medicare program using insurance claims and administrative data /John A. Romley, Abe Dunn, Dana Goldman, and Neeraj Sood ;Valuing housing services in the era of big data: a user cost approach leveraging Zillow microdata /Marina Gindelsky, Jeremy G. Moulton, and Scott A. Wentland --Methodological challenges and advances.Off to the races: a comparison of machine learning and alternative data for predicting economic indicators /Jeffrey C. Chen, Abe Dunn, Kyle Hood, Alexander Driessen, and Andrea Batch ;A machine learning analysis of seasonal and cyclical sales in weekly scanner data /Rishab Guha and Serena Ng ;Estimating the benefits of new products /W. Erwin Diewert and Robert C. Feenstra.